Clinical Data, Inc

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Advertising? Template:Cleanup reorganize Clinical Data Inc is a Healthcare IT Platform company based in the US and operating internationally.[1] It has developed a Clinical Data Standardization & Risk Monitoring Platform called Clindata Cloud.[2] Clindata Cloud makes new drugs affordable by greatly reducing drug development costs and duration.

Designed on big data and cloud computing platforms, Clindata claims that it "compresses clinical trial duration by several months, drives significant cost savings, and improves patient safety through predictive analytics and machine learning algorithms."

Factors Driving New Drug Costs

Clinical Trial Management: Bio-Pharma companies (Sponsors) are required to conduct extensive clinical trials to get their new drugs approved for launch by FDA and other global regulatory agencies such as the European Medicines Agency (EMA)[2] and the Pharmaceuticals and Medical Devices Agency (PMDA) of Japan.[3] It costs over $1.2 billion over 10 years with a success rate of less than 1% to get a new proprietary drug to the market after extensive evidence based clinical trials.

Clinical trials are very complex and involves complex operations such as Patient and Site Recruitment, Supply Chain Management, Regulatory Affairs, Clinical Analytics etc. and should ideally be run by seasoned program and portfolio managers. However program / project management discipline and rigor is often missed on clinical trials leading to huge cost over runs and chronic delays.

Clinical Data Standards:

Large amount of subject centric clinical data is generated throughout the life of a clinical trial / study. However, there is no binding mandatory requirement to submit this clinical data in a standardized format, leading to divergent data submission formats to regulatory agencies such as FDA / EMA / PMDA. This lack of uniformity of submitted data, results in longer review time of NDAs and hence more operational costs and longer duration of the trials.

Site Monitoring Costs:

It is believed that site monitoring costs account for about 20% of the clinical trial budget. Site monitoring involves among other things, 100% source data verification. This is a very exhaustive and expensive process and often prone to errors resulting in FDA citations.

Technology Innovation:

Clinical Trials require several complex, regulatory compliant IT systems such as Electronic Data Management (EDC), master data management, analytics and reporting, study portal, data standardization to name a few. Many smaller bio-pharma and medical device companies cannot afford to have in-house IT expertise or applications; and instead heavily depend on their contract research organization (CROs) for their IT needs as well.

Technologies such as big data, real time predictive analytics and cloud computing could greatly improve the safety and efficiency of clinical trials and need to become mainstream in the clinical trial space.

Manual Data Processing:

The current practice is to manually transform and analyse data from various investigative sites and IT systems. This is mostly an offline exercise done towards the end of a clinical trial. The current FDA rejection rate of New Drug Applications (NDA) due to data related issues stand at 50%, requiring rework and re-submissions leading to further delays and cost over runs.

Clindata Cloud Solution

Regulatory agencies and industry groups have been working for several years to reduce the review time of NDAs and the cost of doing clinical trials. As a result of this effort, a multi pronged approach is being recommended and adopted by the industry.

Clinical Data Standards:

EDI and related data exchange standards such as X12, EDIFACT, ODETTE have enabled organizations around the world to conduct eCommerce for decades. The Bio-Pharma and Medical Devices industry and the regulatory agencies have agreed to finally adopt global standards to exchange clinical data. Beginning October 2016, FDA mandates that all pre-clinical (Animal studies) and clinical data submissions must conform to CDISC data standards.

This helps regulatory agencies create CDISC standards-based tools that help reduce review time. The data standards also help industry submissions be less error prone, hence reducing regulatory rejections. Risk Based Monitoring:

To reduce the burden of site monitoring on clinical trials, the FDA now recommends a risk-based monitoring (RBM) approach. The essence of this recommendation is to gather meaningful metrics that ascertain the safety and welfare of the subjects and performance of the clinical trial, rather than doing 100% source data verification. Adopting RBM may reduce site monitoring costs by 25%. thus reducing overall cost and risk on clinical trials.

Clinical Data Warehouse (CDW):

Many Bio-Pharma companies are realizing that clinical data across multiple sites in a study, cannot exist in data silos and need a mechanism to harmonize and consolidate it to provide a unified data model and view. One way they are trying to address this is by requiring their CROs to build Clinical Data Warehouse for them. Other more IT savvy companies are building their own in-house.

Automatic Data Standardization in real time:

Once the clinical data has been harmonized into a unified subject centric data model, it can be transformed to CDISC compliant data sets. This means that the clinical operations teams at the Bio-Pharma companies can work with standardized data all through the life of the clinical trial than at the very end. Hence a reduced change of FDA rejection and faulty analysis.

Predictive Analytics:

It is possible to mine clinical data to recognize risk patterns that could cause minor or serious adverse events (SEA) in subjects. However it is critical that mined data represent all clinical data across all sites. Housing standardized clinical data in a CDW is a pre-requisite for accurate predictive analytics. This may greatly help clinicians identify subjects at risk of developing SAEs and mitigate that risk, thus improving safety among participating subjects.

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